Spectrum efficiency of a digital wireless communication link is a figure of merit defined as the number of bits of information transmitted per unit of time (second), per unit of bandwidth (Hz), without exceeding a prescribed bit error rate. Spectrum efficiency is measured in bits-per-second-per-Hertz, often written as “bits/s/Hz”. The larger the spectrum efficiency of a wireless link, the more packed the transmitted information in time and bandwidth. A central result of information theory relates spectrum efficiency to the signal quality of the communication channel, usually expressed as signal-to-noise-plus-interference-ratio, or SNIR: the larger SNIR the larger spectrum efficiency.
Theoretically, each wireless transmission between two stations (e.g. a base station and a mobile station in a cellular system) could support all spectrum efficiencies starting from zero (no information transmitted) up to a maximum value determined by the quality of the communication channel during that transmission. Practically, digital wireless systems do not support a continuum of data rates but rather a finite number of data rates, usually specified by standards. Each data rate corresponds to specific spectrum efficiency, with the maximum data rate giving the peak or maximum spectrum efficiency possible for any transmission in the system considered. Operating the wireless system at peak spectrum efficiency for all transmissions, would yield the maximum amount of data that could transfer through wireless connections in the system. This is the maximum capacity of the system. Maximum capacity and peak spectrum efficiency would result if all mobiles were situated next to the base station and all had high channel quality at all times. The actual system capacity, i.e., the actual amount of data that transfers through wireless connections is usually much less than the maximum capacity, as will be discussed next.
Typically, the wireless channel quality in wireless systems changes from transmission to transmission. This effect is especially pronounced in cellular systems where mobiles change their physical location over time and even during transmissions. In this case, rather than focusing on the spectrum efficiency per transmission as an indication of the actual network capacity, it is more meaningful to calculate or measure the average spectrum efficiency for the entire cell over a period. Since all transmissions originate or end in the base station, the cell average spectrum efficiency is directly related to the base station average wireless data traffic.
From inception, commercial cellular systems have operated with low average spectrum efficiency. However, the modest bit-rate demands of traditional voice-dominated communications allowed wireless carriers to mask this shortcoming of their networks for many years. In addition, extra RF spectrum was available to support increases in the wireless traffic without improving the average spectrum efficiency.
The initial limitation of spectrum efficiency in cellular systems was the use of very simple modulation techniques, which only packed very low numbers of bits per allocated RF spectrum. As networks evolved from one generation to another, progressively more sophisticated and more efficient modulation techniques were introduced, improving the peak spectrum efficiency by a large amount, but the network average spectrum efficiency remained low. The reason for this poor average performance is the very nature of the air interface with tiny signals, high noise, presence of interferers, multipath fading, etc.
Following the previous trend, Fourth Generation (4G) wireless systems such as WiMax and LTE (Long Term Evolution) have pushed the transmission schemes to such levels of sophistication that further improvements are unlikely without major penalties in cost and power especially for the mobile devices. For example, 4G systems use multiple RF transceiver schemes called MIMO (Multiple-Input-Multiple-Output) schemes. These employ heavy digital signal processing on several antenna signals, specifically targeting very high peak spectrum efficiency. Nevertheless, even for these systems the average spectrum efficiency remains low compared to the peak efficiency. As already mentioned, this is due to the poor quality of the average communication channel of the air interface. Digital signal processing alone on several antenna signals is not a viable solution to obtaining a substantial increase in overall average spectrum efficiency.
The introduction of smart phones, wireless tablets and other mobile devices capable of accepting and generating large amounts of digital information has produced a profound impact on wireless networks. This, in combination with the heavy use of data hungry wireless applications, is driving the capacity demands of wireless networks to unprecedented levels. The utilization of the limited RF spectrum by traditional low average efficiency methods, including those of existing 4G systems, is no longer appropriate. Operating the networks with average spectrum efficiency, which is far from the peak spectrum efficiency theoretically possible, is simply too wasteful. Furthermore, expanding the traditional wireless networks to accommodate the ever-increasing capacity demands is uneconomical.
In view of the foregoing, it may be understood that there may be significant problems and shortcomings associated with traditional wireless networks.